• Title/Summary/Keyword: SNS(Social Network Service) Data

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Relationships among Perception, Professionalism and Satisfaction with Nail Services Given through Social Network Service and Social Commerce (SNS와 소셜커머스를 통한 네일 서비스의 인식과 전문성 및 만족도와의 관계)

  • Ji-Yeon, Kim
    • Journal of Advanced Technology Convergence
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    • v.1 no.2
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    • pp.89-93
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    • 2022
  • This study attempted to suggest a direction for better services by analyzing correlations among usage patterns, perception, professionalism and satisfaction with nail services given through social media and commerce. For this, a questionnaire survey was performed against women in their 10-50s in Daejeon, Sejong and Chungcheong from October 1 to 20, 2021. A total of 326 copies were used for final analysis The collected data were analyzed, using SPSS 27.0. The results found the followings: As the treatments and products were more specialized, the respondents were more satisfied with services, convenience, treatments and products. Therefore, it is anticipated that the study results would available as basic data which are needed in analyzing correlations among usage patterns, perception, professionalism and satisfaction with nail services given through social media and commerce.

Suggest Schema for Machine Socialization of Technical Development (Machine Socialization 기술개발을 위한 스키마 제안)

  • Park, Sung-hyun;Kim, Yong-Un;Yoo, Sang-keun;Jung, Hoe-kyung
    • Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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    • 2014.10a
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    • pp.865-867
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    • 2014
  • IoT is a kind of business means to maintain the scenario in aware of the situation with the user's through collaboration for M2M have intelligence to each appliance is of machine socializations. The existing IoT Progress from one situation one control of through a simple sensor data, mean from machine socialization is regulate and control on overall the flow of machine manager to solved a scenarios as the situation. In this paper, suggest schema for to apply the M2M of SNS of existing H2H, suggest is schema in information each appliance in solve scenario for machine manager.

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A Study on the Comparison and Semantic Analysis between SNS Big Data, Search Portal Trends and Drug Case Statistics (SNS 빅데이터 및 검색포털 트렌드와 마약류 사건 통계간의 비교 및 의미분석 연구)

  • Choi, Eunjung;Lee, SuRyeon;Kwon, Hyemin;Kim, Myuhngjoo;Lee, Insoo;Lee, Seunghoon
    • Journal of Digital Convergence
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    • v.19 no.2
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    • pp.231-238
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    • 2021
  • SNS data can catch the user's thoughts and actions. And the trend of the search portal is a representative service that can observe the interests of users and their changes. In this paper, the relationship was analyzed by comparing statistics on narcotics incidents and the degree of exposure to narcotics related words in tweets of SNS and in the trends of search portal. It was confirmed that the trend of SNS and search portal trends was the same in the statistics of the prosecution office with a certain time difference.In addition, cluster analysis was performed to understand the meaning of tweets in which narcotics related words were mentioned. In the 50,000 tweets collected in January 2020, it was possible to find meaning related to the sale of actual drugs. Therefore, through SNS monitoring alone it is possible to monitor narcotics-related incidents and to find specific sales or purchase-related information, and this can be used in the investigation process. In the future, it is expected that crime monitoring and prediction systems can be proposed as related crime analysis may be possible not only with text but also images.

Analysis of Performance of Creative Education based on Twitter Big Data Analysis (트위터 빅데이터 분석을 통한 창의적 교육의 성과요인 분석)

  • Joo, Kilhong
    • Journal of Creative Information Culture
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    • v.5 no.3
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    • pp.215-223
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    • 2019
  • The wave of the information age gradually accelerates, and fusion analysis solutions that can utilize these knowledge data according to accumulation of various forms of big data such as large capacity texts, sounds, movies and the like are increasing, Reduction in the cost of storing data accordingly, development of social network service (SNS), etc. resulted in quantitative qualitative expansion of data. Such a situation makes possible utilization of data which was not trying to be existing, and the potential value and influence of the data are increasing. Research is being actively made to present future-oriented education systems by applying these fusion analysis systems to the improvement of the educational system. In this research, we conducted a big data analysis on Twitter, analyzed the natural language of the data and frequency analysis of the word, quantitative measure of how domestic windows education problems and outcomes were done in it as a solution.

The Effects of SNS Advertisement Constituents on Advertising Reliability and Purchase Intention: Focusing on Facebook (SNS 광고 구성요인이 광고 신뢰도와 구매의도에 미치는 영향: 페이스북을 중심으로)

  • Kim, Eun-Hee;Yu, Seung-Yeob
    • Journal of Digital Convergence
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    • v.16 no.5
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    • pp.163-172
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    • 2018
  • This study examined what constitutes the factors of the advertisement of Facebook advertisement, and what factors affect the reliability of the advertisement and the purchase intention. Data were collected from Facebook users and analyzed through exploratory factor analysis and multiple regression analysis. The results of this study are as follows: First, the factors of constituting Facebook advertisement were five factors of advertisement interest, customized information, advertisement exposure, peripheral responsiveness, and product late information. Second, it is confirmed that customized information has a statistically significant effect on ad reliability. However, ad exposure has an adverse effect on ad reliability. Third, customized information and advertising interest had a statistically significant effect on purchase intention. The results of this study have implications for the theoretical development of Facebook advertisement and the basic data for establishing Facebook advertisement strategy.

Personal Information Protection Recommendation System using Deep Learning in POI (POI 에서 딥러닝을 이용한 개인정보 보호 추천 시스템)

  • Peng, Sony;Park, Doo-Soon;Kim, Daeyoung;Yang, Yixuan;Lee, HyeJung;Siet, Sophort
    • Proceedings of the Korea Information Processing Society Conference
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    • 2022.11a
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    • pp.377-379
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    • 2022
  • POI refers to the point of Interest in Location-Based Social Networks (LBSNs). With the rapid development of mobile devices, GPS, and the Web (web2.0 and 3.0), LBSNs have attracted many users to share their information, physical location (real-time location), and interesting places. The tremendous demand of the user in LBSNs leads the recommendation systems (RSs) to become more widespread attention. Recommendation systems assist users in discovering interesting local attractions or facilities and help social network service (SNS) providers based on user locations. Therefore, it plays a vital role in LBSNs, namely POI recommendation system. In the machine learning model, most of the training data are stored in the centralized data storage, so information that belongs to the user will store in the centralized storage, and users may face privacy issues. Moreover, sharing the information may have safety concerns because of uploading or sharing their real-time location with others through social network media. According to the privacy concern issue, the paper proposes a recommendation model to prevent user privacy and eliminate traditional RS problems such as cold-start and data sparsity.

Design and Implementation of Recommending Potential Friends by Using Spatiotemporal Data (시공간 데이터를 이용한 잠재적 친구 추천 설계 및 구현)

  • Yeo, Eunji;Choi, Young-Hwan;Lim, Hyo-Sang
    • Proceedings of the Korea Information Processing Society Conference
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    • 2013.11a
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    • pp.1129-1131
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    • 2013
  • 온라인 상에서 불특정 타인과 관계를 맺을 수 있는 서비스로 소셜 네트워크 서비스(Social Network Service : SNS)가 새롭게 떠오르고 있다. 1990년대에 등장한 SNS는 최근에는 스마트폰을 이용한 모바일 서비스로 인해 이용자의 수가 급격히 늘어나고 있다. SNS에서는 '친구 찾기' 라는 서비스를 제공하는데, 이는 이용자의 개인정보를 분석하여 이용하여 친구를 찾아주는 서비스이다. 기존의 '친구 찾기' 서비스는 이용자가 제공하는 정보만을 다른 이용자의 정보와 비교하여 친구를 찾았다. 그러나 이용자가 제공하는 정보는 한정적이기 때문에 비교할 수 있는 정보의 양도 한정되어 찾을 수 있는 친구의 수에도 한계가 생긴다. 그래서 본 논문에서는 단순한 개인정보 비교를 통한 친구를 찾는 방법이 아닌 이용자가 제공하는 시공간 데이터를 활용하여 추론을 통해 친구를 추천해주는 시스템을 설계하고 구현한다.

The Sensitivity Analysis for Customer Feedback on Social Media (소셜 미디어 상 고객피드백을 위한 감성분석)

  • Song, Eun-Jee
    • Journal of the Korea Institute of Information and Communication Engineering
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    • v.19 no.4
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    • pp.780-786
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    • 2015
  • Social media, such as Social Network Service include a lot of spontaneous opinions from customers, so recent companies collect and analyze information about customer feedback by using the system that analyzes Big Data on social media in order to efficiently operate businesses. However, it is difficult to analyze data collected from online sites accurately with existing morpheme analyzer because those data have spacing errors and spelling errors. In addition, many online sentences are short and do not include enough meanings which will be selected, so established meaning selection methods, such as mutual information, chi-square statistic are not able to practice Emotional Classification. In order to solve such problems, this paper suggests a module that can revise the meanings by using initial consonants/vowels and phase pattern dictionary and meaning selection method that uses priority of word class in a sentence. On the basis of word class extracted by morpheme analyzer, these new mechanisms would separate and analyze predicate and substantive, establish properties Database which is subordinate to relevant word class, and extract positive/negative emotions by using accumulated properties Database.

A Study on the Service Status of the Spatial Open Platform based on the Analysis of Web Server User Log: 2014.5.20.~2014.6.2. Log Data (웹 사용자 로그 분석 기반 공간정보 오픈플랫폼 서비스 사용현황 연구: 2014.5.20.~2014.6.2. 수집자료 대상)

  • Lee, Seung Han;Cho, Tae Hyun;Kim, Min Soo
    • Spatial Information Research
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    • v.22 no.4
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    • pp.67-76
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    • 2014
  • Recently, through the development of IT and mobile technology, spatial information plays a role of infrastructure of the people life and the national economy. Many kinds of applications including SNS and social commerce is to leverage the spatial information for their services. In the case of domestic, spatial open platform that can provide national spatial data infrastructure services in a stable manner has been released. And many people have been interested to the open platform services. However, the open platform currently has many difficulties to analyze its service status and load in real time, because it does not hold a real-time monitoring system. Therefore, we propose a method that can analyze the real-time service status of the open platform using the analysis of the web server log information. In particular, we propose the results of the analysis as follows: amount of data transferred, network bandwidth, number of visitors, hit count, contents usage, and connection path. We think the results presented in this study is insufficient to understand the perfect service status of the open platform. However, it is expected to be utilized as the basic data for understanding of the service status and for system expansion of the open platform, every year.

Social Media Bigdata Analysis Based on Information Security Keyword Using Text Mining (텍스트마이닝을 활용한 정보보호 키워드 기반 소셜미디어 빅데이터 분석)

  • Chung, JinMyeong;Park, YoungHo
    • Journal of Korea Society of Industrial Information Systems
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    • v.27 no.5
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    • pp.37-48
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    • 2022
  • With development of Digital Technology, social issues are communicated through digital-based platform such as SNS and form public opinion. This study attempted to analyze big data from Twitter, a world-renowned social network service, and find out the public opinion. After collecting Twitter data based on 14 keywords for 1 year in 2021, analyzed the term-frequency and relationship among keyword documents with pearson correlation coefficient using Data-mining Technology. Furthermore, the 6 main topics that on the center of information security field in 2021 were derived through topic modeling using the LDA(Latent Dirichlet Allocation) technique. These results are expected to be used as basic data especially finding key agenda when establishing strategies for the next step related industries or establishing government policies.